Grammatical Error Correction

Grammatical Error Correction (GEC) is the task of correcting different kinds of errors in text such as spelling, punctuation, grammatical, and word choice errors.

GEC is typically formulated as a sentence correction task. A GEC system takes a potentially erroneous sentence as input and is expected to transform it to its corrected version. See the example given below:

| Input (Erroneous) | Output (Corrected) | | ------------------------- | ---------------------- | |She see Tom is catched by policeman in park at last night. | She saw Tom caught by a policeman in the park last night.|

Papers

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Showing 201–225 of 415 papers

Title	Date	Tasks	Status
New Dataset and Strong Baselines for the Grammatical Error Correction of Russian	Aug 1, 2021	Grammatical Error Correction	—Unverified
Noisy Channel for Low Resource Grammatical Error Correction	Aug 1, 2019	Grammatical Error CorrectionLanguage Modeling	—Unverified
Non-Autoregressive Grammatical Error Correction Toward a Writing Support System	Dec 1, 2020	Grammatical Error Correction	—Unverified
Numerically Grounded Language Models for Semantic Error Correction	Aug 14, 2016	Fact CheckingGrammatical Error Correction	—Unverified
NUS at the HOO 2012 Shared Task	Jun 1, 2012	Grammatical Error Correction	—Unverified
On Assessing and Developing Spoken ’Grammatical Error Correction’ Systems	Jul 1, 2022	Grammatical Error Correctionspeech-recognition	—Unverified
On the application of Large Language Models for language teaching and assessment technology	Jul 17, 2023	Grammatical Error CorrectionMisinformation	—Unverified
On the (In)Effectiveness of Large Language Models for Chinese Text Correction	Jul 18, 2023	Grammatical Error Correction	—Unverified
Overview of NLP-TEA 2016 Shared Task for Chinese Grammatical Error Diagnosis	Dec 1, 2016	Grammatical Error Correction	—Unverified
Overview of NLPTEA-2018 Share Task Chinese Grammatical Error Diagnosis	Jul 1, 2018	Grammatical Error CorrectionPosition	—Unverified
Overview of the NLP-TEA 2015 Shared Task for Chinese Grammatical Error Diagnosis	Jul 1, 2015	Grammatical Error CorrectionGrammatical Error Detection	—Unverified
Personalizing Grammatical Error Correction: Adaptation to Proficiency Level and L1	Jun 4, 2020	Grammatical Error Correction	—Unverified
Phrase-based Machine Translation is State-of-the-Art for Automatic Grammatical Error Correction	May 20, 2016	Grammatical Error CorrectionMachine Translation	—Unverified
Phrase Structure Annotation and Parsing for Learner English	Aug 1, 2016	Grammatical Error CorrectionPart-Of-Speech Tagging	—Unverified
Position Offset Label Prediction for Grammatical Error Correction	Oct 1, 2022	Data AugmentationDecoder	—Unverified
POSTECH Grammatical Error Correction System in the CoNLL-2014 Shared Task	Jun 1, 2014	Grammatical Error CorrectionLanguage Modelling	—Unverified
Predicting Compact Phrasal Rewrites with Large Language Models for ASR Post Editing	Jan 23, 2025	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Proficiency Matters Quality Estimation in Grammatical Error Correction	Jan 17, 2022	Grammatical Error Correction	—Unverified
Prompting open-source and commercial language models for grammatical error correction of English learner text	Jan 15, 2024	Grammatical Error Correction	—Unverified
Proofread Sentence Generation as Multi-Task Learning with Editing Operation Prediction	Nov 1, 2017	ArticlesGrammatical Error Correction	—Unverified
ProQE: Proficiency-wise Quality Estimation dataset for Grammatical Error Correction	Jun 1, 2022	Grammatical Error Correction	—Unverified
Pseudo-Bidirectional Decoding for Local Sequence Transduction	Jan 31, 2020	DecoderGrammatical Error Correction	—Unverified
Pseudo-Error Generation for Grammatical Error Correction Based on Learner’s First Language	Sep 17, 2021	Grammatical Error CorrectionTranslation	—Unverified
RACAI GEC -- A hybrid approach to Grammatical Error Correction	Jun 1, 2014	Grammatical Error CorrectionGrammatical Error Detection	—Unverified
Reducing Sequence Length by Predicting Edit Operations with Large Language Models	May 19, 2023	Formality Style TransferGrammatical Error Correction	—Unverified

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All datasets CoNLL-2014 Shared Task BEA-2019 (test)Falko-MERLIN JFLEG UA-GEC CoNLL-2014 Shared Task (10 annotations)Restricted Unrestricted _Restricted_EstGEC-L2 FCGEC MuCGEC

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	Ensembles of best 7 models + GRECO + GTP-rerank	F0.5	72.8	—	Unverified
2	Majority-voting ensemble on best 7 models	F0.5	71.8	—	Unverified
3	GRECO (voting+ESC)	F0.5	71.12	—	Unverified
4	GEC-DI (LM+GED)	F0.5	69.6	—	Unverified
5	Unsupervised GEC + cLang8	F0.5	69.6	—	Unverified
6	ESC	F0.5	69.51	—	Unverified
7	T5	F0.5	68.87	—	Unverified
8	MoECE	F0.5	67.79	—	Unverified
9	SynGEC	F0.5	67.6	—	Unverified
10	Sequence tagging + token-level transformations + two-stage fine-tuning (+BERT, RoBERTa, XLNet)	F0.5	66.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Majority-voting ensemble on best 7 models	F0.5	81.4	—	Unverified
2	GRECO (voting+ESC)	F0.5	80.84	—	Unverified
3	ESC	F0.5	79.9	—	Unverified
4	RedPenNet	F0.5	77.6	—	Unverified
5	clang_large_ft2-gector	F0.5	77.1	—	Unverified
6	Unsupervised GEC + cLang8	F0.5	76.5	—	Unverified
7	DeBERTa + RoBERTa + XLNet	F0.5	76.05	—	Unverified
8	MoECE	F0.5	74.07	—	Unverified
9	Sequence tagging + token-level transformations + two-stage fine-tuning (+RoBERTa, XLNet)	F0.5	73.7	—	Unverified
10	BEA Combination	F0.5	73.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Llama + 1M BT + gold	F0.5	76.75	—	Unverified
2	mT5-based multimodal MoE	F0.5	76.3	—	Unverified
3	gT5 xxl	F0.5	75.96	—	Unverified
4	Transformer	F0.5	73.71	—	Unverified
5	Transformer - synthetic pretrain only	F0.5	51.41	—	Unverified
6	Multilayer Convolutional Encoder-Decoder	F0.5	43.35	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	VERNet	GLEU	62.1	—	Unverified
2	Transformer + Pre-train with Pseudo Data + BERT	GLEU	62	—	Unverified
3	SMT + BiGRU	GLEU	61.5	—	Unverified
4	Copy-augmented Model (4 Ensemble +Denoising Autoencoder)	GLEU	61	—	Unverified
5	Transformer	GLEU	59.9	—	Unverified
6	CNN Seq2Seq	GLEU	57.47	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Llama + 1M BT + gold	F0.5	74.09	—	Unverified
2	mBART-based model with synthetic data	F0.5	68.17	—	Unverified
3	mT5 large + 10M synth	F0.5	68.09	—	Unverified
4	RedPenNet	F0.5	67.71	—	Unverified
5	ChatGPT (zero-shot)	F0.5	27.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	GRECO (vote+ESC)	F0.5	85.21	—	Unverified
2	SMT + BiGRU	F0.5	72.04	—	Unverified
3	CNN Seq2Seq	F0.5	70.14	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CNN Seq2Seq + Quality Estimation	F0.5	56.52	—	Unverified
2	Transformer	F0.5	55.8	—	Unverified
3	+ BIFI with no critic	F0.5	18.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CNN Seq2Seq + Fluency Boost and inference	GLEU	62.37	—	Unverified
2	CNN Seq2Seq + Fluency Boost	F0.5	61.34	—	Unverified
3	+ BIFI (ours)	F0.5	42.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Transformer	GLEU	59.9	—	Unverified
2	CNN Seq2Seq	GLEU	57.47	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Llama + 1M BT + gold	F0.5	69.97	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	STG-Joint	exact match	34.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	GEC-DI (LM+GED)	F0.5	48.61	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RedPenNet	F0.5	77.6	—	Unverified